an investigation into the use of serum albumin in pressure sore prediction

An investigation into the use of serumalbumin in pressure sore prediction

Denis Anthony RMN RGN BA MSc PhD AMIEE

The Mary Seacole Research Centre, School of Nursing and Midwifery,

De Montfort University, Leicester

Tim Reynolds BSc MB ChB MD MRCPath

Professor of Chemical Pathology, Queen's Hospital, Burton on Trent

and Linda Russell SRN BSc

Tissue Viability Nurse, Queen's Hospital, Burton on Trent, England

Accepted for publication 21 January 2000

ANTHONYANTHONY DD., REYNOLDSREYNOLDS TT. && RUSSELLRUSSELL L. (2000)L. (2000) Journal of Advanced Nursing 32(2),

359±365

An investigation into the use of serum albumin, in pressure sore prediction

Objectives To ascertain the relevance of serum albumin and serum sodium as

predictors of pressure sores in addition to the Waterlow score. Design Obser-

vational study of patients at risk of developing decubitus ulcers. Setting Staf-

fordshire, in the midlands of the United Kingdom. Participants 773 elderly

hospital in-patients of a district general hospital. Measurements Waterlow

scores and serum albumin and sodium. Development of a pressure sore.

Results Logistic regression analysis of serum albumin, serum sodium and the

Waterlow score showed the Waterlow score and serum albumin were signi®cant

predictors of pressure sores. Conclusions Serum albumin may, in this patient

group (in-patients over 64 years of age), be a useful predictor of pressure sore

occurrence, though further work is needed to establish whether this is the case.

Risk assessment of pressure sores can possibly be improved by adding serum

albumin to one of the pre-existing tools such as the Waterlow score.

Keywords: pressure sore, serum albumin, risk assessment, Waterlow score,

tissue viability, decubitus ulcer, prediction

INTRODUCTION

Serum albumin is the single most common method to

assess nutrition (Thomas 1997) and has been the subject of

a number of studies evaluating its importance, in pressure

sore risk assessment. The role of nutrition in the preven-

tion and treatment of pressure sores is a contentious issue.

There have been many reviews of nutrition with speci®c

reference to serum albumin (McLaren 1992, Lewis &

Harding 1993, Pinchcofsky-Devin 1994, Lewis 1996,

Strauss & Margolis 1996, Thomas 1997). From these

reviews it is clear that there is a relationship between

serum albumin and pressure sores, but it is much less

obvious that serum albumin is a predictor of pressure sores.

It has been known since the 1930s that patients who

have low serum albumin are more likely to develop

breakdown of wounds (Thompson et al. 1938a, 1938b)

and that patients with pressure sores have low serum

albumin concentrations (Mulholland et al. 1943). Further-

more, low serum albumin is associated with mortality

(Strauss & Margolis 1996). Many subsequent cross-

sectional studies have shown that patients with pressure

Correspondence: Denis Anthony, The Mary Seacole Research Centre,

School of Nursing and Midwifery, Charles Frears Campus, De Montfort

University, 266 London Road, Leicester LE2 1RQ, England.

Ó 2000 Blackwell Science Ltd 359

Journal of Advanced Nursing, 2000, 32(2), 359±365 Methodological issues in nursing research

sores have lower serum albumin than patients with no

sores. For example, regression analyses, in long-stay

patients who received extra nutritional support, indicated

albumin, mobility, activity and food intake as predictors

for pressure sores (Ek et al. 1991). However, protein may

be lost from sores (Strauss & Margolis 1996) and certain

conditions such as cachexia may cause both pressure sores

and poor absorption of nutrients (including protein)

(Strauss & Margolis 1996, Thomas 1997). It is unclear

therefore whether low protein levels cause pressures

sores, or pressures sores cause low protein levels, or

whether both are caused by a third factor.

An index of malnutrition based on biochemical and

anthropometric values did show predictive value in a

prospective study, and the two groups of malnourished

and non-malnourished were similar in terms of comor-

bidity, implying a real effect of malnutrition and not

simply a proxy for morbidity (Thomas et al. 1995). How-

ever, no single biochemical marker has been found for

pressure sores (Strauss & Margolis 1996). Prospective

studies of serum albumin and other univariate predictors

such as body mass index (BMI) have shown con¯icting

results (Thomas 1997). For example, serum albumin has

been found to be a positive predictive factor, in pressure

sores (Allman et al. 1986), but other studies show no

predictive value (Guralnik et al. 1988, Berlowitz & Wil-

king 1989, Allman et al. 1995). One problem with serum

albumin is its long half life of 21 days (Lewis 1996), and

possibly for this reason (Thomas 1997) improving nutri-

tional intake is not necessarily associated with an increase

in serum albumin.

It has been shown in animal studies, that being subjec-

ted to more than 4 hours of pressure invariably causes

sores, but the severity of the sore was greater in malnour-

ished animals (Takeda et al. 1992). As malnutrition is

associated with worse sores in animals, one might expect

albumin to be correlated with grade of sore, and in cross-

sectional studies (Pinchcofsky-Devin & Kaminski 1986)

this has been shown, but in a prospective study no

correlation was seen (Myers et al. 1990). Thomas (1997)

reported that no study has shown that increasing nutrition

prevents sores, though it can help to heal existing sores.

THE STUDY

Method

The Hospital Information Support System (HISS) in a

Staffordshire trust (Queen's Hospital, Burton-on-Trent)

allowed routinely collected data to be analysed. These

data included serum albumin, serum sodium, the Water-

low score and whether the patient had a sore on admis-

sion, or acquired one during admission.

Every patient was assessed using the Waterlow score on

admission to hospital: this is a mandatory ®eld in the

Hospital Information Support System (HISS) and cannot

be bypassed. Waterlow scores used in this study were all

taken on admission. Grading of pressure sores used the

Torrance score (Torrance 1983). A full day education

programme with ward nurses on pressure sore prevention

addressing the Waterlow and Torrance scores had been

carried out before data collection.

Albumin data were taken from routine laboratory tests,

performed as an admission pro®le on all acute medical

and all admissions aged 65 or over as a baseline from

which to monitor changes. Analysis was on a Beckman

CX-7 (Beckman Instruments Ltd, High Wycombe, UK)

using Beckman albumin reagents. Data were stored on the

main HISS computer and downloaded to an Access

database, whence it was matched with the pressure sore

®les. Serum sodium was measured on a Beckman CX-7 by

indirect ion-selective electrode.

Analyses were completed using SPSS for Windows

(version 9á0) and included logistic regression and receiver

operating characteristic (ROC). In all inferential testing

signi®cance was de®ned as a probability of less than 0á05.

Forward stepwise logistic regression using the Wald

method used a variable entry P-value of 0á05 and a

removal P-value of 0á10. A full model was also computed.

ROC curves are created by measuring the sensitivity and

speci®city of an assessment tool at various thresholds.

There are several basic texts on ROC (Swets 1979, Zweig &

Campbell 1993, Altman & Bland 1994a, 1994b, Rose 1995,

Anthony 1999). The normalized area under the ROC curve

gives a quantitative measure of the classi®cation ability of

the tool. A value of 0á5 (or 50%) indicates random

classi®cation, and a value above this is better than

random, with a perfect classi®cation shown by a value

of 1á0 or 100%.

Sample

The ®rst admission of any patient admitted in the period

30 July 1996 to 6 September 1997 was used. Analysis for

the remainder of this paper concentrates on the 773

patients who did not have a sore on admission, were over

64 years of age, and were admitted for a hospital stay of at

least 7 days (median 12, interquartile range 8±18, maxi-

mum 111) and for whom complete data on serum albumin,

sodium, Waterlow scores and pressure sore status were

available. This group contained 113 hospital acquired

sores. The sample is a convenience sample in that it

consists of all the patients admitted in the period prior to

the analysis that were available on the HISS.

RESULTS

Serum albumin, serum sodium and Waterlow score were

all found to be approximately normally distributed so

parametric tests were indicated. Student's t-test for

D. Anthony et al.

360 Ó 2000 Blackwell Science Ltd, Journal of Advanced Nursing, 32(2), 359±365

independent groups (two tailed) showed no signi®cant

differences between those patients who acquired a sore

and those who did not for serum sodium, but for serum

albumin (P < 0á001) and the Waterlow score (P < 0á001),

signi®cant differences were seen, with higher Waterlow

scores and lower albumin values for patients who devel-

oped sores, see Figure 1 and Figure 2.

Using chi-square (Pearson's method used as expected

values in all cases exceeded ®ve), neither gender (P� 0á37)

nor hypoalbuminaemia (de®ned as <32 g/dL, P� 0á094)

were signi®cantly different between patients who later

developed pressure sores and those who did not, but

hyponatraemia (de®ned as <135 g/dL, P� 0á049) was

signi®cant.

The frequencies of grades of sore are shown in Table 1.

Using Spearman (as grade is not normally distributed)

rank correlations (two tailed) there were signi®cant corre-

lations for grade of sore against serum albumin (rs�±0á129, P < 0á001) and Waterlow score (rs� 0á297,

P < 0á001).

Using a logistic regression and entering serum albu-

min, serum sodium and the Waterlow score, both the

Waterlow (P < 0á0001) and serum albumin (P� 0á009)

were signi®cant, but not serum sodium (P� 0á55) or the

constant (P� 0á99). Using the forward Wald method only

the Waterlow score (P < 0á0001) and serum albumin

(P� 0á0063) were kept in the logistic regression equa-

tion. Adding a binary variable for hyponatraemia

(de®ned above, and again using the forward Wald

method) did not change the result, only the Waterlow

score and serum albumin remained in the logistic

regression equation.

The odds ratios for both serum albumin and the Water-

low score are given, see Table 2. The Waterlow odds ratio

is about 1á18 (rounded to 2 decimal places). A patient with

a borderline at risk Waterlow score of 10 would have about

one-®fth the risk of developing a sore than a patient with a

very high risk Waterlow score of 20. If the serum albumin

odds ratio of 0á95 (again rounded to 2 decimal places) is

Figure 1 Waterlow scores for sores vs. no sores. Boxplots show

the median, interquartile range, outliers, and extreme cases of

individual variables. In the case of Figures 1 and 2 they show

Waterlow and serum albumin for two groups, those with and

those without sores. In each case it gives a graphic demonstration

of the difference of the two groups with respect to (in these cases)

the Waterlow score and serum albumin. The interquartile range

(i.e. where half the data lie) is shown in a box, and a line across

the box indicates the median. The whiskers are lines that extend

1á5 box lengths from the upper or lower edge of the box. Values

beyond these are shown as individual cases, either outliers (up to

3 box lengths) or extreme values (more than 3 box lengths, shown

as asterisks, though no extreme values occur in these ®gures).

Figure 2 Serum albumin for sores vs. no sores.

Table 1 Frequencies of grades

Grade Frequency % Cumulative %t

No sore 663 85á8 85á81 38 4á9 90á72 37 4á8 95á53 27 3á5 99á04 7 0á9 99á95 1 0á1 100á0

Total 773 100á0

Table 2 Odds ratios for signi®cant variables

Odds ratio

Lower 95% CI

for odds ratio

Upper 95% CI

for odds ratio

Albumin 0á9465 0á9033 0á9918

Waterlow 1á1763 1á1250 1á2300

Methodological issues in nursing research Serum albumin in pressure sore prediction

Ó 2000 Blackwell Science Ltd, Journal of Advanced Nursing, 32(2), 359±365 361

used, then decreasing serum albumin by 10 would

increase pressure sore risk by about two-thirds.

The probability function returned by the logistic

regression was used to classify the patients at a variety

of thresholds (each discrete value returned by the

function was a separate threshold) as was each value

of serum albumin and each Waterlow score. Sensitivity

and speci®cities were computed for each threshold of

each assessment method. ROC curves were created (see

Figure 3) and areas under the ROC curves calculated

(see Table 4).

DISCUSSION

Despite problems with serum albumin (e.g. the long half

life of serum albumin) and in this study low numbers of

hypoalbuminaemic patients (93á7% were in the normal

range), adding serum albumin to the Waterlow score

improved the predictive ability. The area under the ROC

curve is greater for the predictive equation obtained by

logistic regression than for either serum albumin or the

Waterlow score alone (see Figure 3 and Table 3) and the

ROC curves in each case were signi®cantly different from

0á5 (see Table 4).

From Figure 3 one may see that for a sensitivity of 0á8 the

logistic prediction based on both albumin and Waterlow

has a speci®city of about 0á65, while the Waterlow alone

has a speci®city of about 0á50 (the Waterlow score that

gives this speci®city is between 11 and 12). This would

mean, in this sample, that about 430 of the 660 patients

with no sores would correctly be identi®ed by the logistic

prediction, and only 330 of those assessed by Waterlow

alone, so the increase in speci®city would enable scarce

resources to be better targeted at the patients who will go

on to develop sores. Conversely for a given speci®city of

(say) 0á5, the logistic prediction has a sensitivity of about

0á86 compared with 0á80 for the Waterlow. In this sample,

for a speci®city of 0á5 about 90 of the 113 patients would

be correctly identi®ed by Waterlow, but 97 would be

Table 3 ROC areas

Score ROC area

Albumin 0á596

Waterlow 0á729

Waterlow and albumin

(logistic regression predicted value)

0á741

Figure 3 ROC curves for Waterlow score, albumin and regression equation using Waterlow score and albumin. )�Waterlow;

� logistic prediction; � serum albumin.

D. Anthony et al.


identi®ed by the logistic prediction. So nine more patients

could be given extra support.

However, the change in the ROC curves is small, and

the signi®cance of any improvement needs to be

addressed. SPSS version 9 gives 95% con®dence limits

for ROC curves (see Table 4, and) but does not allow

direct comparisons between the curves. It may be that

although the areas under the individual curves are

signi®cantly different from 0á5 (the value returned from

a random classi®cation) little or no difference exists

among the areas under the ROC curves for (say) Water-

low and Waterlow plus serum albumin. However, in the

logistic regression analysis adding serum albumin does

give a signi®cant improvement over the Waterlow score

alone.

To use albumin in clinical practice it may be necessary

to categorize the albumin into ranges. This has been done

here for both the Waterlow score and serum albumin in

Table 5 and Table 7, and the area under the ROC curves,

respectively, in Table 6 and Table 8. It is seen that the

areas under the ROC curves remain signi®cant.

The Waterlow score has a nutrition sub-score, which

is a very crude assessment of the patient based on the

nurse's observation of the body build, with no labor-

atory or anthropometric analysis. It would be useful to

assess the relevance of this sub-score and compare it

with serum albumin in a prospective study. Data are

currently being collected in Birmingham to address this

problem.

One might create a modi®ed risk indicator based on

Waterlow and serum albumin. Recent work on the

Waterlow score components in a similar sample

(Anthony Clark & Dallender 2000) suggest only about

three of the components of the Waterlow score are

useful (continence, skin assessment and appetite, the

last of which gives further evidence of the importance of

nutrition). It is possible that a reduced set of compo-

nents of the Waterlow score added to serum albumin

may give greater predictive power than the Waterlow

score alone.

Limitations

The study is restricted to elderly in-patients and is

therefore not necessarily generalizable to other groups.

In particular, elderly residents in nursing homes may

show very different nutrition pro®les. The sub-scores of

the Waterlow score were not available from the HISS, and

Table 4 Area under the ROC

curves Asymptotic 95% con®dence interval

Area SDSD Signi®cance Lower bound Upper bound

Logistic regression

Predicted value 0á741 0á024 P < 0á001 0á694 0á787

Waterlow score 0á729 0á038 P < 0á001 0á654 0á803

Serum albumin 0á596 0á030 0á001 0á538 0á654

Table 5 Sensitivity and speci®city of Waterlow scores at ®ve

levels

Threshold Sensitivity 1 Ð Speci®city

0 1á000 0á000

10 0á920 0á315

15 0á646 0á732

20 0á195 0á939

25 0á035 0á994

Table 6 Area under the ROC curve: Waterlow ranges

Asymptotic 95% con®dence interval


0á723 0á025 P < 0á001 0á673 0á772

Table 8 Area under the ROC curve: albumin ranges

Asymptotic 95% con®dence interval


0.577 0á030 0á009 0á517 0á636

Table 7 Sensitivity and speci®city of albumin ranges at ®ve

levels

Threshold Sensitivity Speci®city

0 1á000 0á000

20 0á593 0á311

25 0á257 0á878

30 0á044 0á965

35 0á018 0á986



therefore only an analysis of total Waterlow score was

possible.

The sample used in this study may include patients

with low serum albumin due to liver disease, diabetes

mellitus, and those on diuretics. Because of the heterogen-

eity of the sample, one should interpret these results with

caution, and further studies of more focused groups are

indicated.

Appropriate interventions and high quality nursing care

could in¯uence the incidence of pressure sores which in

turn would show the risk assessment tool to be poorly

performing with respect to sensitivity and speci®city

(Edwards 1996). To determine true sensitivity and spe-

ci®city would mean withholding preventive intervention

and allowing pressure sores to develop in vulnerable

patients, which would be ethically unacceptable (Flana-

gan 1995).

CONCLUSIONS

Serum albumin has been shown to be predictive, in

pressure sores. Adding serum albumin to the Waterlow

score may improve the predictive value of the Waterlow

score in this group (elderly in-patients). However, this has

not been proven in this study, and requires further

evaluation.

There are resource implications of adding elements to

the existing Waterlow score. However, many patients are

already assessed for serum albumin, and the cost of the

laboratory test is low (approximately £0á60 at 1999 prices).

The addition of serum albumin in assessing this group of

patients is therefore not costly.

Acknowledgements

The data were provided by the Burton NHS Trust HISS.

One of the authors (DA) is a recipient of a Smith & Nephew

Foundation fellowship for this and other analyses.

Two of the authors (TR and LR) received a proportion

of their funding from the NHS Executive; the views

expressed in this publication are those of the authors and

not necessarily those of the NHS Executive.

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